An embodiment relates to detection of a road surface condition using adaptive learning techniques.
Precipitation on driving surface causes several different issues for a vehicle. For example, water or snow on a road reduces the coefficient of friction between the tires of the vehicle and the surface of the road resulting in vehicle stability issues.
Various techniques are known for attempting to determine what the environmental condition of the road surface is. An example of one such technique is a vehicle model that senses vehicle operating conditions to obtain data for classifying a road surface condition. The model has set parameters and without any updates, the model would yield the same results for a given input. Therefore, if the model misdiagnoses the road surface condition, then the output will continuously generate the same incorrect result.
Other approaches, such as an image-based approach, utilize a classifier to determine the road surface condition. However, if the classifier is not updated, then the classifier will output the same result even if it is incorrect.
In such cases, the road surface detection system is entirely dependent on the classifier or model stored in the vehicle when the vehicle was manufactured or brought in for a service update.